基于灰度梯度正则化去噪的改进数字图像相关法 下载: 1076次
郑成林, 何顶顶, 费庆国. 基于灰度梯度正则化去噪的改进数字图像相关法[J]. 光学学报, 2018, 38(8): 0812002.
Chenglin Zheng, Dingding He, Qingguo Fei. Improved Digital Image Correlation Method Based on Gray Gradient Denoised by Regularization Method[J]. Acta Optica Sinica, 2018, 38(8): 0812002.
[1] Khoo S W, Karuppanan S, Tan C S. A review of surface deformation and strain measurement using two-dimensional digital image correlation[J]. Metrology and Measurement Systems, 2016, 23(3): 461-480.
Khoo S W, Karuppanan S, Tan C S. A review of surface deformation and strain measurement using two-dimensional digital image correlation[J]. Metrology and Measurement Systems, 2016, 23(3): 461-480.
[3] Guo X, Liang J, Tang Z Z, et al. High-temperature digital image correlation method for full-field deformation measurement captured with filters at 2600 ℃ using spraying to form speckle patterns[J]. Optical Engineering, 2014, 53(6): 063101.
Guo X, Liang J, Tang Z Z, et al. High-temperature digital image correlation method for full-field deformation measurement captured with filters at 2600 ℃ using spraying to form speckle patterns[J]. Optical Engineering, 2014, 53(6): 063101.
[4] 邵新星, 戴云彤, 何小元, 等. 实时数字图像相关用于土木准静态实验测量[J]. 光学学报, 2015, 35(10): 1012003.
邵新星, 戴云彤, 何小元, 等. 实时数字图像相关用于土木准静态实验测量[J]. 光学学报, 2015, 35(10): 1012003.
[8] Su Y, Zhang Q C, Xu X H, et al. Quality assessment of speckle patterns for DIC by consideration of both systematic errors and random errors[J]. Optics and Lasers in Engineering, 2016, 86: 132-142.
Su Y, Zhang Q C, Xu X H, et al. Quality assessment of speckle patterns for DIC by consideration of both systematic errors and random errors[J]. Optics and Lasers in Engineering, 2016, 86: 132-142.
[9] 徐小海, 苏勇, 蔡玉龙, 等. 数字图像相关法测量局域变形场中形函数和模板尺寸的影响[J]. 力学学报, 2015, 47(5): 848-862.
徐小海, 苏勇, 蔡玉龙, 等. 数字图像相关法测量局域变形场中形函数和模板尺寸的影响[J]. 力学学报, 2015, 47(5): 848-862.
Xu X H, Su Y, Cai Y L, et al. Influence of shape functions and template size in digital image correlation method for highly inhomogeneous deformations[J]. Chinese Journal of Theoretical and Applied Mechanics, 2015, 47(5): 848-862.
[11] 苏勇, 张青川, 徐小海, 等. 数字图像相关技术中插值偏差的理论估计[J]. 力学学报, 2016, 48(2): 495-510.
苏勇, 张青川, 徐小海, 等. 数字图像相关技术中插值偏差的理论估计[J]. 力学学报, 2016, 48(2): 495-510.
Su Y, Zhang Q C, Xu X H, et al. Theoretical estimation of interpolation bias error in digital image correlation[J]. Chinese Journal of Theoretical and Applied Mechanics, 2016, 48(2): 495-510.
[14] Baldi A A, Bertolino F. A posteriori compensation of the systematic error due to polynomial interpolation in digital image correlation[J]. Optical Engineering, 2013, 52(10): 101913.
Baldi A A, Bertolino F. A posteriori compensation of the systematic error due to polynomial interpolation in digital image correlation[J]. Optical Engineering, 2013, 52(10): 101913.
[18] Shao X X, Dai X J, He X Y. Noise robustness and parallel computation of the inverse compositional Gauss-Newton algorithm in digital image correlation[J]. Optics and Lasers in Engineering, 2015, 71: 9-19.
Shao X X, Dai X J, He X Y. Noise robustness and parallel computation of the inverse compositional Gauss-Newton algorithm in digital image correlation[J]. Optics and Lasers in Engineering, 2015, 71: 9-19.
[19] Mazzoleni P, Matta F, Zappa E, et al. Gaussian pre-filtering for uncertainty minimization in digital image correlation using numerically-designed speckle patterns[J]. Optics and Lasers in Engineering, 2015, 66: 19-33.
Mazzoleni P, Matta F, Zappa E, et al. Gaussian pre-filtering for uncertainty minimization in digital image correlation using numerically-designed speckle patterns[J]. Optics and Lasers in Engineering, 2015, 66: 19-33.
[20] Su Y, Zhang Q C, Xu X H, et al. Interpolation bias for the inverse compositional Gauss-Newton algorithm in digital image correlation[J]. Optics and Lasers in Engineering, 2018, 100: 267-278.
Su Y, Zhang Q C, Xu X H, et al. Interpolation bias for the inverse compositional Gauss-Newton algorithm in digital image correlation[J]. Optics and Lasers in Engineering, 2018, 100: 267-278.
[25] Schreier HW, Orteu JJ, Sutton MA. Image correlation for shape, motion and deformation measurements[M]. New York: Springer, 2009: 101- 103.
Schreier HW, Orteu JJ, Sutton MA. Image correlation for shape, motion and deformation measurements[M]. New York: Springer, 2009: 101- 103.
[26] Burden RL, Faires JD. Numerical analysis[M]. 9 th ed. Boston: Brooks/Cole , 2011: 174- 185.
Burden RL, Faires JD. Numerical analysis[M]. 9 th ed. Boston: Brooks/Cole , 2011: 174- 185.
[27] Cullum J. Numerical differentiation and regularization[J]. SIAM Journal on Numerical Analysis, 1971, 8(2): 254-265.
Cullum J. Numerical differentiation and regularization[J]. SIAM Journal on Numerical Analysis, 1971, 8(2): 254-265.
[28] Zhou P, Goodson K E. Subpixel displacement and deformation gradient measurement using digital image/speckle correlation (DISC)[J]. Optical Engineering, 2001, 40(8): 1613-1620.
Zhou P, Goodson K E. Subpixel displacement and deformation gradient measurement using digital image/speckle correlation (DISC)[J]. Optical Engineering, 2001, 40(8): 1613-1620.
郑成林, 何顶顶, 费庆国. 基于灰度梯度正则化去噪的改进数字图像相关法[J]. 光学学报, 2018, 38(8): 0812002. Chenglin Zheng, Dingding He, Qingguo Fei. Improved Digital Image Correlation Method Based on Gray Gradient Denoised by Regularization Method[J]. Acta Optica Sinica, 2018, 38(8): 0812002.